Industry Costs of Equity: Incorporating Prior Information

Abstract

This paper examines whether incorporating economically motivated prior information yields more accurate forecasts of industry costs of equity. I find that incorporating the long-run mean of the CAPM parameters and the industry characteristics in the cross-section produces more accurate parameter estimates, which subsequently translate into a more accurate out-of-sample forecast of the industry costs of equity. The outperformance of this method over rolling-window estimates becomes larger as the forecast horizon extends into the future. These findings provide evidence that the CAPM parameters have a long-run mean-reversion property, and are correlated with the industry characteristics in a systematic way.